Microphone arrays have been widely studied because of their effectiveness in enhancing the quality of the captured audio signal. The use of multiple spatially distributed microphones allows spatial filtering, filtering based on direction, along with conventional temporal filtering, which can better reject interference or noise signals. This results in an overall improvement of the captured sound quality of the target or desired signal.
Beamforming operations are applicable to processing the signals of a number of sensor arrays, including microphone arrays, sonar arrays, directional radio antenna arrays, radar arrays, and so forth. For example, in the case of a microphone array, beamforming involves processing audio signals received at the microphones of the array in such a way as to make the microphone array act as a highly directional microphone. In other words, beamforming provides a “listening beam” which points to, and receives, a particular sound source while attenuating other sounds and noise, including, for example, reflections, reverberations, interference, and sounds or noise coming from other directions or points outside the primary beam. Pointing of such beams is typically referred to as beamsteering. A generic beamformer automatically designs a set of beams (i.e., beamforming) that cover a desired angular space range in order to better capture the target or desired signal.
Various microphone array processing algorithms have been proposed to improve the quality of the target signal. The generalized sidelobe canceller (GSC) architecture has been especially popular. The GSC is an adaptive beamformer that keeps track of the characteristics of interfering signals and then attenuates or cancels these interfering signals using an adaptive interference canceller (AIC). This greatly improves the target signal, the signal one wishes to obtain. However, if the actual direction of arrival (DOA) of the target signal is different from the expected DOA, a considerable portion of the target signal will leak into the adaptive interference canceller, which results in target signal cancellation and hence a degraded target signal. Although the GSC is good at rejecting directional interference signals, its noise suppression capability is not very good if there is isotropic ambient noise.
A minimum variance distortionless response (MVDR) beamformer is another widely studied and used beamforming algorithm. Assuming the direction of arrival (DOA) of the desired signal is known, the MVDR beamformer estimates the desired signal while minimizing the variance of the noise component of the formed estimate. In practice, however, the DOA of the desired signal is not known exactly, which significantly degrades the performance of the MVDR beamformer. Much research has been done into a class of algorithms known as robust MVDR. As a general rule, these algorithms work by extending the region where the source can be located. Nevertheless, even assuming perfect sound source localization (SSL), the fact that the sensors may have distinct, directional responses adds yet another level of uncertainty that the MVDR beamformer is not able to handle well. Commercial arrays solve this by using a linear array of microphones, all pointing at the same direction, and therefore with similar directional gain. Nevertheless, for the circular geometry used in some microphone arrays, especially in the realm of video conferencing, this directionality is accentuated because each microphone has a significantly different direction of arrival in relation to the desired source. Experiments have shown that MVDR and other existing algorithms perform well when omnidirectional microphones are used, but do not provide much enhancement when directional microphones are used.